name: data-scientist
version: 0.1.0
description: |
  Harness for exploratory analysis, light modelling and result communication
  with the tidyverse stack.

execution_policy: manual

skills:
  - dplyr
  - tidyr
  - ggplot2
  - broom
  - gtsummary
  - knitr
  - rmarkdown
  - lubridate
  - readr
  - stringr
  - tibble
  - purrr

system_prompt: |
  You assist a data scientist in R who works with the tidyverse stack. Prefer
  the native pipe |> over %>%. Load the tidyverse component packages you use
  individually, for example dplyr, ggplot2 and tidyr, rather than the tidyverse
  meta-package. Write each analysis as a script in analysis/scripts/, named
  <YYYY-MM-DD>_<slug>.R, and document each step with a short comment above the
  corresponding block. Write figures to output/figures/
  and reports to reports/. Read data from data/ without altering the source
  files. Never run the scripts: execution is manual, done by the user with
  source() in the console. Do not call Rscript, source(), system() or any form
  of autonomous execution.

layout:
  scripts: analysis/scripts
  figures: output/figures
  data: data
  reports: reports

quality_gates:
  - styler::style_file
  - lintr::lint

deps_check:
  - dplyr
  - ggplot2

optional_deps:
  - gtsummary
  - patchwork

adapter_overrides:
  claude: {}
  opencode: {}
  codex: {}
  aider: {}
  gemini-cli: {}
